Literature Review: Investigating Drug Transport at the Blood-Brain Barrier and the Effects of P-glycoprotein on the Brain Distribution of Drugs.

The blood-brain barrier (BBB) is a unique barrier that strictly regulates the entry of endogenous substrates and xenobiotics into the brain. This is due to its tight junctions and the array of transporters and metabolic enzymes that are expressed. The determination of brain concentrations in vivo is difficult, laborious and expensive which means that there is interest in developing predictive tools of brain distribution. Predicting brain concentrations is important even in early drug development to ensure efficacy of central nervous system (CNS) targeted drugs and safety of non-CNS drugs. The literature review covers the most common current in vitro, in vivo and in silico methods of studying transport into the brain, concentrating on transporter effects. The consequences of efflux mediated by p-glycoprotein, the most widely characterized transporter expressed at the BBB, is also discussed. The aim of the experimental study was to build a pharmacokinetic (PK) model to describe p-glycoprotein substrate drug concentrations in the brain using commonly measured in vivo parameters of brain distribution. The possibility of replacing in vivo parameter values with their in vitro counterparts was also studied. All data for the study was taken from the literature. A simple 2-compartment PK model was built using the Stella™ software. Brain concentrations of morphine, loperamide and quinidine were simulated and compared with published studies. Correlation of in vitro measured efflux ratio (ER) from different studies was evaluated in addition to studying correlation between in vitro and in vivo measured ER. A Stella™ model was also constructed to simulate an in vitro transcellular monolayer experiment, to study the sensitivity of measured ER to changes in passive permeability and Michaelis-Menten kinetic parameter values. Interspecies differences in rats and mice were investigated with regards to brain permeability and drug binding in brain tissue. Although the PK brain model was able to capture the concentration-time profiles for all 3 compounds in both brain and plasma and performed fairly well for morphine, for quinidine it underestimated and for loperamide it overestimated brain concentrations. Because the ratio of concentrations in brain and blood is dependent on the ER, it is suggested that the variable values cited for this parameter and its inaccuracy could be one explanation for the failure of predictions. Validation of the model with more compounds is needed to draw further conclusions. In vitro ER showed variable correlation between studies, indicating variability due to experimental factors such as test concentration, but overall differences were small. Good correlation between in vitro and in vivo ER at low concentrations supports the possibility of using of in vitro ER in the PK model. The in vitro simulation illustrated that in the simulation setting, efflux is significant only with low passive permeability, which highlights the fact that the cell model used to measure ER must have low enough paracellular permeability to correctly mimic the in vivo situation.

Sensitivity of wetland methane emissions to model assumptions: application and model testing against site observations

Abstract. Methane emissions from natural wetlands and rice paddies constitute a large proportion of atmospheric methane, but the magnitude and year-to-year variation of these methane sources is still unpredictable. Here we describe and evaluate the integration of a methane biogeochemical model (CLM4Me; Riley et al., 2011) into the Community Land Model 4.0 (CLM4CN) in order to better explain spatial and temporal variations in methane emissions. We test new functions for soil pH and redox potential that impact microbial methane production in soils. We also constrain aerenchyma in plants in always-inundated areas in order to better represent wetland vegetation. Satellite inundated fraction is explicitly prescribed in the model because there are large differences between simulated fractional inundation and satellite observations. A rice paddy module is also incorporated into the model, where the fraction of land used for rice production is explicitly prescribed. The model is evaluated at the site level with vegetation cover and water table prescribed from measurements. Explicit site level evaluations of simulated methane emissions are quite different than evaluating the grid cell averaged emissions against available measurements. Using a baseline set of parameter values, our model-estimated average global wetland emissions for the period 1993–2004 were 256 Tg CH4 yr−1, and rice paddy emissions in the year 2000 were 42 Tg CH4 yr−1. Tropical wetlands contributed 201 Tg CH4 yr−1, or 78 % of the global wetland flux. Northern latitude (>50 N) systems contributed 12 Tg CH4 yr−1. We expect this latter number may be an underestimate due to the low high-latitude inundated area captured by satellites and unrealistically low high-latitude productivity and soil carbon predicted by CLM4. Sensitivity analysis showed a large range (150–346 Tg CH4 yr−1) in predicted global methane emissions. The large range was sensitive to: (1) the amount of methane transported through aerenchyma, (2) soil pH (± 100 Tg CH4 yr−1), and (3) redox inhibition (± 45 Tg CH4 yr−1).